Jakob Zeitler

I research methods and limitations of causal inference and their intersection with machine learning.

I believe that causal inference can work in the real world only if we are honest about its assumptions. That is why I am looking at problem settings with trustworthy properties:

• Partial identification is a very attractive alternative to full identification due to weaker assumptions.
• New directions such as Causal Bayesian Optimisation or Synthetic Control will play a crucial role in the future.
• I also find topological perspectives on causal inference particularly useful for understanding limits of causal inference.

Message me at mail@firstname-lastname.de